⚡️ Speed up function sorter by 56,821%

[codeflash-ai]

📄 56,821% (568.21x) speedup for sorter in codeflash/bubble_sort.py

⏱️ Runtime : 727 milliseconds → 1.28 milliseconds (best of 768 runs)

📝 Explanation and details

Here's a faster version using Python's built-in sort, which is highly optimized (Timsort, O(n log n)), compared to the original bubble sort (O(n²)). This preserves the function signature and all behavior as required.

Explanation:

• arr.sort() sorts the list in-place using Timsort, which is much faster than bubble sort for practical input sizes.
• No unnecessary loops or swaps; the function is both optimal in runtime and memory usage.
• All existing side effects, such as printed output, are preserved.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 49 Passed
⏪ Replay Tests	✅ 3 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import random  # for generating large random lists
import sys  # for testing with max/min values

# imports
import pytest  # used for our unit tests
from codeflash.bubble_sort import sorter

# -----------------
# Basic Test Cases
# -----------------

def test_sorter_empty_list():
    # Test sorting an empty list
    arr = []
    codeflash_output = sorter(arr.copy()) # 3.62μs -> 2.83μs (27.9% faster)

def test_sorter_single_element():
    # Test sorting a list with one element
    arr = [42]
    codeflash_output = sorter(arr.copy()) # 3.96μs -> 2.83μs (39.7% faster)

def test_sorter_already_sorted():
    # Test sorting an already sorted list
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()) # 4.12μs -> 2.96μs (39.5% faster)

def test_sorter_reverse_sorted():
    # Test sorting a reverse sorted list
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()) # 4.50μs -> 2.88μs (56.5% faster)

def test_sorter_unsorted():
    # Test sorting an unsorted list
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()) # 4.42μs -> 2.88μs (53.6% faster)

def test_sorter_with_duplicates():
    # Test sorting a list with duplicate elements
    arr = [4, 2, 5, 2, 1, 4]
    codeflash_output = sorter(arr.copy()) # 5.17μs -> 2.96μs (74.7% faster)

def test_sorter_negative_numbers():
    # Test sorting a list with negative numbers
    arr = [-3, -1, -2, 0, 2, 1]
    codeflash_output = sorter(arr.copy()) # 4.58μs -> 3.04μs (50.7% faster)

def test_sorter_mixed_sign_numbers():
    # Test sorting a list with both positive and negative numbers
    arr = [0, -10, 5, -3, 8, 2]
    codeflash_output = sorter(arr.copy()) # 5.04μs -> 2.96μs (70.5% faster)

def test_sorter_all_equal():
    # Test sorting a list with all elements equal
    arr = [7, 7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()) # 3.88μs -> 2.79μs (38.8% faster)

# -----------------
# Edge Test Cases
# -----------------

def test_sorter_large_numbers():
    # Test sorting a list with very large (and small) integers
    arr = [sys.maxsize, -sys.maxsize - 1, 0, 999999999, -999999999]
    codeflash_output = sorter(arr.copy()) # 5.25μs -> 3.21μs (63.7% faster)

def test_sorter_floats_and_ints():
    # Test sorting a list with both floats and ints
    arr = [3, 1.5, 2, 4.2, 0]
    codeflash_output = sorter(arr.copy()) # 5.75μs -> 3.42μs (68.3% faster)

def test_sorter_negative_zero():
    # Test sorting a list with -0.0 and 0.0 (should be treated as equal)
    arr = [0.0, -0.0, 1.0, -1.0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.96μs -> 3.00μs (65.3% faster)
    # Python treats 0.0 == -0.0 as True, so order doesn't matter

def test_sorter_minimal_difference():
    # Test sorting a list with minimal differences (floating point precision)
    arr = [1.0000001, 1.0, 1.0000002]
    codeflash_output = sorter(arr.copy()) # 4.75μs -> 3.33μs (42.5% faster)

def test_sorter_strings():
    # Test sorting a list of strings (should sort lexicographically)
    arr = ['banana', 'apple', 'cherry']
    codeflash_output = sorter(arr.copy()) # 4.50μs -> 2.92μs (54.3% faster)

def test_sorter_mixed_types_raises():
    # Test sorting a list with incomparable types (should raise TypeError)
    arr = [1, 'a', 3.5]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_nested_lists_raises():
    # Test sorting a list with nested lists (should raise TypeError)
    arr = [1, [2], 3]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_tuple_elements():
    # Test sorting a list of tuples (should sort by first element)
    arr = [(2, 'b'), (1, 'a'), (3, 'c')]
    codeflash_output = sorter(arr.copy()) # 4.92μs -> 3.42μs (43.9% faster)

def test_sorter_stability():
    # Test that the sort is stable (relative order of equal elements is preserved)
    arr = [('a', 2), ('b', 1), ('c', 2), ('d', 1)]
    # Sort by second element, so ('b', 1) should come before ('d', 1), etc.
    expected = [('b', 1), ('d', 1), ('a', 2), ('c', 2)]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.96μs -> 3.50μs (41.7% faster)

# -----------------
# Large Scale Test Cases
# -----------------

def test_sorter_large_sorted():
    # Test sorting a large already sorted list
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()) # 51.5μs -> 28.0μs (84.4% faster)

def test_sorter_large_reverse():
    # Test sorting a large reverse sorted list
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()) # 19.8ms -> 27.7μs (71315% faster)

def test_sorter_large_random():
    # Test sorting a large random list
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 16.9ms -> 57.9μs (29155% faster)

def test_sorter_large_duplicates():
    # Test sorting a large list with many duplicate values
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 14.6ms -> 47.3μs (30700% faster)

def test_sorter_large_negative():
    # Test sorting a large list of negative numbers
    arr = [random.randint(-10000, -1) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 15.8ms -> 56.2μs (27929% faster)

def test_sorter_large_floats():
    # Test sorting a large list of floats
    arr = [random.uniform(-10000, 10000) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()) # 16.0ms -> 265μs (5932% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import random  # used for generating large scale random lists
import string  # used for string sorting tests
import sys  # used for maxsize/minsize edge cases

# imports
import pytest  # used for our unit tests
from codeflash.bubble_sort import sorter

# unit tests

# ------------------------
# 1. Basic Test Cases
# ------------------------

def test_sorter_empty_list():
    """Test sorting an empty list."""
    arr = []
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.79μs -> 2.83μs (33.8% faster)

def test_sorter_single_element():
    """Test sorting a list with a single element."""
    arr = [42]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.88μs -> 2.92μs (32.8% faster)

def test_sorter_already_sorted():
    """Test sorting an already sorted list."""
    arr = [1, 2, 3, 4, 5]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.83μs -> 2.92μs (31.4% faster)

def test_sorter_reverse_sorted():
    """Test sorting a reverse sorted list."""
    arr = [5, 4, 3, 2, 1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.83μs -> 2.92μs (65.7% faster)

def test_sorter_unsorted_list():
    """Test sorting a typical unsorted list."""
    arr = [3, 1, 4, 5, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.00μs -> 2.96μs (35.2% faster)

def test_sorter_with_duplicates():
    """Test sorting a list with duplicate values."""
    arr = [2, 3, 2, 1, 3]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.17μs -> 2.79μs (49.2% faster)

def test_sorter_with_negative_numbers():
    """Test sorting a list with negative numbers."""
    arr = [-2, -5, 3, 0, 2]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.17μs -> 2.96μs (40.8% faster)

def test_sorter_all_identical():
    """Test sorting a list where all elements are identical."""
    arr = [7, 7, 7, 7]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 3.88μs -> 2.92μs (32.8% faster)

# ------------------------
# 2. Edge Test Cases
# ------------------------

def test_sorter_large_and_small_integers():
    """Test sorting a list with very large and very small integers."""
    arr = [sys.maxsize, -sys.maxsize-1, 0, 999999, -999999]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.17μs -> 3.25μs (59.0% faster)
    expected = [-sys.maxsize-1, -999999, 0, 999999, sys.maxsize]

def test_sorter_floats_and_integers():
    """Test sorting a list with both integers and floats."""
    arr = [3.2, 1, 4.5, 2, 0.0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 6.25μs -> 3.54μs (76.5% faster)

def test_sorter_negative_zero_and_zero():
    """Test sorting a list with 0 and -0.0 (should be treated as equal)."""
    arr = [0, -0.0, 1, -1]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.42μs -> 3.12μs (41.3% faster)

def test_sorter_strings():
    """Test sorting a list of strings."""
    arr = ["banana", "apple", "cherry", "date"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.54μs -> 3.12μs (45.3% faster)

def test_sorter_strings_case_sensitivity():
    """Test sorting a list of strings with different cases."""
    arr = ["banana", "Apple", "cherry", "Date"]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.42μs -> 3.04μs (45.2% faster)

def test_sorter_empty_and_nonempty_strings():
    """Test sorting a list with empty and non-empty strings."""
    arr = ["", "a", "abc", ""]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 4.12μs -> 2.88μs (43.5% faster)

def test_sorter_nested_lists_error():
    """Test sorting a list with nested lists (should raise TypeError)."""
    arr = [1, [2], 3]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_mixed_types_error():
    """Test sorting a list with mixed incompatible types (should raise TypeError)."""
    arr = [1, "a", 3]
    with pytest.raises(TypeError):
        sorter(arr.copy())

def test_sorter_nan_and_infinity():
    """Test sorting a list with NaN and Infinity."""
    arr = [float('nan'), float('inf'), -float('inf'), 0]
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 5.00μs -> 3.08μs (62.2% faster)

def test_sorter_custom_objects_error():
    """Test sorting a list with custom objects that do not support comparison (should raise TypeError)."""
    class Dummy:
        pass
    arr = [Dummy(), Dummy()]
    with pytest.raises(TypeError):
        sorter(arr.copy())

# ------------------------
# 3. Large Scale Test Cases
# ------------------------

def test_sorter_large_sorted_list():
    """Test sorting a large already sorted list."""
    arr = list(range(1000))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 52.2μs -> 27.5μs (89.4% faster)

def test_sorter_large_reverse_sorted_list():
    """Test sorting a large reverse sorted list."""
    arr = list(range(999, -1, -1))
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 19.7ms -> 27.5μs (71306% faster)

def test_sorter_large_random_list():
    """Test sorting a large list of random integers."""
    arr = random.sample(range(-10000, -9000), 1000)
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 16.7ms -> 56.6μs (29406% faster)

def test_sorter_large_list_with_duplicates():
    """Test sorting a large list with many duplicate values."""
    arr = [random.choice([1, 2, 3, 4, 5]) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 14.3ms -> 46.0μs (30950% faster)

def test_sorter_large_list_of_strings():
    """Test sorting a large list of random strings."""
    arr = [''.join(random.choices(string.ascii_letters, k=5)) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 17.7ms -> 88.5μs (19872% faster)

def test_sorter_large_identical_elements():
    """Test sorting a large list where all elements are identical."""
    arr = [42] * 1000
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 50.5μs -> 26.6μs (89.5% faster)

def test_sorter_large_floats():
    """Test sorting a large list of random floats."""
    arr = [random.uniform(-1e6, 1e6) for _ in range(1000)]
    expected = sorted(arr)
    codeflash_output = sorter(arr.copy()); result = codeflash_output # 15.9ms -> 281μs (5546% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

⏪ Replay Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
test_tracer_py__replay_test_0.py::test_codeflash_bubble_sort_sorter	559ms	136μs	✅410178%

To edit these changes git checkout codeflash/optimize-sorter-mcnucrk3 and push.